An information-theoretic approach to combining object models

被引:2
作者
Kruppa, H [1 ]
Schiele, B [1 ]
机构
[1] ETH Zurich, Perceptual Comp & Comp Vis Grp, Zurich, Switzerland
关键词
model combination; robust vision; mutual information;
D O I
10.1016/S0921-8890(02)00204-X
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper introduces a new method for combining different object models. By determining a configuration of the models, which maximizes their mutual information, the proposed method creates a unified hypothesis from multiple object models on the fly without prior training. To validate the effectiveness of the proposed method, experiments are conducted in which human faces are detected and localized in images by combining different face models. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:195 / 203
页数:9
相关论文
共 17 条
  • [1] [Anonymous], 2000, P IEEE C COMP VIS PA
  • [2] BREGLER C, 1996, ADV NEURAL INFORMATI
  • [3] CHOUDHURY T, 1999, P 2 INT C AUD VID BA
  • [4] COUTAZ J, 1997, P IEEE C COMP VIS PA, P100
  • [5] Cover T. M., 2005, ELEM INF THEORY, DOI 10.1002/047174882X
  • [6] Hart P.E., 1973, Pattern recognition and scene analysis
  • [7] Statistical pattern recognition: A review
    Jain, AK
    Duin, RPW
    Mao, JC
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2000, 22 (01) : 4 - 37
  • [8] JORDAN M, 1994, NEURAL COMPUTATION, V6
  • [9] On combining classifiers
    Kittler, J
    Hatef, M
    Duin, RPW
    Matas, J
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1998, 20 (03) : 226 - 239
  • [10] Probabilistic visual learning for object representation
    Moghaddam, B
    Pentland, A
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1997, 19 (07) : 696 - 710